Luke Zettlemoyer
RESEARCH MANAGER | SEATTLE, UNITED STATES
Luke Zettlemoyer is a research manager and site lead for FAIR Seattle. He is also a Professor in the Allen School of Computer Science & Engineering at the University of Washington. His research is in empirical computational semantics, where the goal is to build models that recover representations of the meaning of natural language text. Recent work has focused on language modeling pretraining, multi-lingual NLP, semantic parsing, question answering, and information extraction. Luke's honors include a PECASE Award and being named an Allen Distinguished Investigator, along with more than ten paper awards at top NLP venues. He was a postdoctoral researcher at the University of Edinburgh and received his Ph.D. from MIT.
Research Areas
Luke's Publications
September 05, 2024
CONVERSATIONAL AI
NLP
Transfusion: Predict the Next Token and Diffuse Images with One Multi-Modal Model
Chunting Zhou, Lili Yu, Arun Babu, Kushal Tirumala, Michihiro Yasunaga, Leonid Shamis, Jacob Kahn, Luke Zettlemoyer, Omer Levy, Xuezhe Ma
September 05, 2024
August 01, 2024
NLP
The Belebele Benchmark: a Parallel Reading Comprehension Dataset in 122 Language Variants
Lucas Bandarkar, Davis Liang, Benjamin Muller, Mikel Artetxe, Satya Narayan Shukla, Don Husa, Naman Goyal, Abhinandan Krishnan, Luke Zettlemoyer, Madian Khabsa
August 01, 2024
April 22, 2024
NLP
Text Quality-Based Pruning for Efficient Training of Language Models
Vasu Sharma *, Karthik Padthe *, Newsha Ardalani, Kushal Tirumala, Russ Howes, Hu Xu, Bernie Huang, Daniel Li (FAIR), Armen Aghajanyan, Gargi Ghosh, Luke Zettlemoyer
April 22, 2024
February 22, 2024
NLP
Toolformer: Language Models Can Teach Themselves to Use Tools
Timo Schick, Jane Yu, Roberto Dessì, Roberta Raileanu, Maria Lomeli, Eric Hambro, Luke Zettlemoyer, Nicola Cancedda, Thomas Scialom
February 22, 2024
December 04, 2023
NLP
PATHFINDER: Guided Search over Multi-Step Reasoning Paths
Olga Golovneva, Sean O'Brien, Ram Pasunuru, Tianlu Wang, Luke Zettlemoyer, Maryam Fazel-Zarandi, Asli Celikyilmaz
December 04, 2023
November 17, 2023
NLP
FactScore: Fine-grained Atomic Evaluation of Factual Precision in Long Form Text Generation
Scott Yih, Luke Zettlemoyer, Mike Lewis, Hannaneh Hajishirzi, Kalpesh Krishna, Mohit Iyyer, Pang Wei Koh, Sewon Min, Xinxi Lyu
November 17, 2023
October 27, 2023
CONVERSATIONAL AI
NLP
XLM-V: Overcoming the Vocabulary Bottleneck in Multilingual Masked Language Models
Davis Liang, Hila Gonen, Yuning Mao, Rui Hou, Naman Goyal, Marjan Ghazvininejad, Luke Zettlemoyer, Madian Khabsa
October 27, 2023
September 03, 2023
NLP
COMPUTER VISION
Retrieval-Augmented Multimodal Language Modeling
Michihiro Yasunaga, Armen Aghajanyan, Weijia Shi, Rich James, Jure Leskovec, Percy Liang, Mike Lewis, Luke Zettlemoyer, Scott Yih
September 03, 2023
July 14, 2023
NLP
COMPUTER VISION
Scaling Autoregressive Multi-Modal Models: Pretraining and Instruction Tuning
Lili Yu, Bowen Shi, Ram Pasunuru, Benjamin Miller, Olga Golovneva, Tianlu Wang, Arun Babu, Binh Tang, Brian Karrer, Shelly Sheynin, Candace Ross, Adam Polyak, Russ Howes, Vasu Sharma, Jacob Xu, Uriel Singer, Daniel Li (FAIR), Gargi Ghosh, Yaniv Taigman, Maryam Fazel-Zarandi, Asli Celikyilmaz, Luke Zettlemoyer, Armen Aghajanyan
July 14, 2023
November 16, 2022
RESEARCH
NLP
Memorization Without Overfitting: Analyzing the Training Dynamics of Large Language Models
Kushal Tirumala, Aram H. Markosyan, Armen Aghajanyan, Luke Zettlemoyer
November 16, 2022
June 25, 2022
Quantifying Adaptability in Pre-trained Language Models with 500 Tasks
Jane Yu, Alon Halevy, Luke Zettlemoyer, Madian Khabsa, Belinda Li, Jacob Andreas
June 25, 2022
December 03, 2021
Bilingual Lexicon Induction via Unsupervised Bitext Construction and Word Alignment
Sida Wang, Haoyue Shi, Luke Zettlemoyer
December 03, 2021
October 26, 2021
NLP
Luna: Linear Unified Nested Attention
Xuezhe Ma, Xiang Kong, Sinong Wang, Chunting Zhou, Jonathan May, Hao Ma, Luke Zettlemoyer
October 26, 2021
December 06, 2020
RESEARCH
NLP
Pre-training via Paraphrasing
Michael Lewis, Armen Aghajanyan, Gargi Ghosh, Luke Zettlemoyer, Marjan Ghazvininejad, Sida Wang
December 06, 2020
November 16, 2020
RESEARCH
NLP
Scalable Zero-shot Entity Linking with Dense Entity Retrieval
Ledell Wu, Fabio Petroni, Luke Zettlemoyer, Sebastian Riedel, Martin Josifoski
November 16, 2020
July 15, 2020
RESEARCH
ML APPLICATIONS
Aligned Cross Entropy for Non-Autoregressive Machine Translation
Marjan Ghazvininejad, Luke Zettlemoyer, Omer Levy, Vladimir Karpukhin
July 15, 2020
July 09, 2020
NLP
ML APPLICATIONS
Emerging Cross-lingual Structure in Pretrained Language Models
Shijie Wu, Haoran Li, Luke Zettlemoyer, Shijie Wu, Ves Stoyanov
July 09, 2020
July 06, 2020
RESEARCH
NLP
Simple and Effective Retrieve-Edit-Rerank Text Generation
Marjan Ghazvininejad, Luke Zettlemoyer, Nabil Hossain
July 06, 2020
June 25, 2020
NLP
Moving Down the Long Tail of Word Sense Disambiguation with Gloss Informed Bi-encoders
Terra Blevins, Luke Zettlemoyer
June 25, 2020
March 02, 2020
RESEARCH
ML APPLICATIONS
Generalization through Memorization: Nearest Neighbor Language Models
Mike Lewis, Luke Zettlemoyer, Omer Levy, Dan Jurafsky, Urvashi Khandelwal
March 02, 2020
November 02, 2019
RESEARCH
NLP
Mask-Predict: Parallel Decoding of Conditional Masked Language Models
Marjan Ghazvininejad, Luke Zettlemoyer, Omer Levy, Yinhan Liu
November 02, 2019
October 23, 2019
RESEARCH
SPEECH & AUDIO
Cloze-driven Pretraining of Self-attention Networks
Michael Auli, Alexei Baevski, Luke Zettlemoyer, Sergey Edunov, Yinhan Liu
October 23, 2019
October 18, 2019
RESEARCH
SPEECH & AUDIO
A Discrete Hard EM Approach for Weakly Supervised Question Answering
Luke Zettlemoyer, Danqi Chen, Hanna Hajishirzi, Sweon Min
October 18, 2019
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